Sensitivity Analysis

Here, we run a variety of sensitivity analyses on the original and time-averaged networks. This code has been adapted from Peeples, Matthew A. 2017. Network Science and Statistical Techniques for Dealing with Uncertainties in Archaeological Datasets. [online]. Available: www.mattpeeples.net/netstats.html. One main difference is that we use igraph rather than the sna and network packages.

Load and prepare data for sensitivity analysis.

# First, load in all of the the igraph objects. However, we will only use Prignano_ta_graphs, as the first network for each time period will be the original graph.
load("../Data/Prignano_graph_objects.RData")

# The lists are unnested for 1 level.
Prignano.nets <- Prignano_ta_graphs[[1]]

# Give names to each list for each time period to keep track.
Prignano.names <- c("EIA1E", "EIA1L", "EIA2", "OA", "AA")
names(Prignano.nets) <- Prignano.names

prignano.names.full <- 
c("EIA1E_network_1", "EIA1E_network_2", "EIA1E_network_3", "EIA1E_network_4", 
"EIA1E_network_5", "EIA1L_network_1", "EIA1L_network_2a", "EIA1L_network_2b", 
"EIA1L_network_3a", "EIA1L_network_3b", "EIA1L_network_4a", "EIA1L_network_4b", 
"EIA1L_network_5", "EIA2_network_1", "EIA2_network_2a", "EIA2_network_2b", 
"EIA2_network_3a", "EIA2_network_3b", "EIA2_network_3c", "EIA2_network_4a", 
"EIA2_network_4b", "EIA2_network_5", "OA_network_1", "OA_network_2a", 
"OA_network_2b", "OA_network_3a", "OA_network_3b", "OA_network_4a", 
"OA_network_4b", "OA_network_5", "AA_network_1", "AA_network_2", 
"AA_network_3", "AA_network_4", "AA_network_5")

Functions to get multiple centrality scores for binary networks.

Functions for creating outputs

Function for creating plots

Potential Impact of Missing Nodes

Over multiple centrality measures and/or networks

## `summarise()` has grouped output by 'orig.net', 'num.net'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'orig.net', 'num.net'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'orig.net', 'num.net'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'orig.net', 'num.net'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'orig.net', 'num.net'. You can override using the `.groups` argument.

## Saving 10.5 x 7.5 in image

Potential impact of missing edges